Loyalty programs nowadays are an important instrument for gaining and retaining new and existing customers and are, therefore, increasingly gaining in importance.
Combining different loyalty programs in a targeted manner opens up access to loyalty systems for a company that improve customer retention and attraction of new customers.
One most important, already available program for retaining top and steady customers is the bonus or rebate marketing, for example. Such a bonus or rebate marketing offers the consumer the advantage that an overall outstanding value of the provided services is offered by the provider, thereby resulting in a competitive advantage for the provider.
One important business sector in which to apply such a method is the current telecommunications sector. Because of the continuing downward trend of prices for the services that are being made available in this sector and increasingly more advantageous contract conditions for the customer, a relatively high fluctuation of existing customers between telecommunications providers can be seen for such services.
A reduction in customer fluctuation and/or retention and expansion of existing customers can be achieved, for example, through the use of a loyalty program that provides for crediting the customer or user with earned bonuses.
Administering such loyalty programs is therefore applicable and advantageous also in the field of IP-based systems.
In future IP-based systems, such as IMS (IP Multimedia Subsystem), criteria for crediting loyalty bonuses can be defined and also incorporated relatively easily.
Such criteria for crediting loyalty bonuses are, for example, call data, such as the duration, time intervals, the date, month and/or year.
It is known that a method and system for collecting user behavior during run-time are performed in the mobile 3GPP IP-based multimedia subsystem by means of an online server. This online server (OSAS: Online Statistics and Advertisement Server) is an application server component that is integrated into the IMS session and into the corresponding signaling traffic. This OSAS has the significant advantage that the user behavior can be viewed online during the run-time and not only in offline mode, like with the CDR analysis (Call Detailed Record) that is known from the prior art, which has a delay of, at times, several hours.
With an OSAS it is possible, for example, to collect relevant statistical data in a communication system and perform an analysis of the user behavior during the run-time of the application.
An OSAS can therefore also be used for analyzing the call behavior of a user, with the OSAS performing the collection, analysis and presentation of all customer data online and nearly in real time to provide complete web statistics for customers who utilized web-based services, as well as a detailed break-down of the origin of the users, both according to geographical factors and broken down by firms and organizations. Consequently, these recorded statistical data can also be used for a bonus program for crediting a bonus to the user based on the user's call behavior.
This method has the significant shortcoming, however, that an analysis of the determined run-time data and comparison with stored profile data from different loyalty programs can be implemented only by means of an auxiliary function.